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  1. Plot the decision boundaries of a VotingClassif...

    Plot the decision boundaries of a VotingClassifier for two features of the Iris dataset. Plot the class probabilities of the first sample in a toy dataset predicted by three different classifiers a...
    scikit-learn.org/stable/auto_examples/ensemble/plot_voting_decision_regions.html
    Fri Nov 22 23:53:27 UTC 2024
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  2. Agglomerative clustering with different metrics...

    Demonstrates the effect of different metrics on the hierarchical clustering. The example is engineered to show the effect of the choice of different metrics. It is applied to waveforms, which can b...
    scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering_metrics.html
    Fri Nov 22 23:53:27 UTC 2024
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  3. Two-class AdaBoost — scikit-learn 1.5.2 documen...

    This example fits an AdaBoosted decision stump on a non-linearly separable classification dataset composed of two “Gaussian quantiles” clusters (see sklearn.datasets.make_gaussian_quantiles) and pl...
    scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html
    Fri Nov 22 23:53:27 UTC 2024
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  4. Early stopping in Gradient Boosting — scikit-le...

    Gradient Boosting is an ensemble technique that combines multiple weak learners, typically decision trees, to create a robust and powerful predictive model. It does so in an iterative fashion, wher...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_early_stopping.html
    Fri Nov 22 23:53:26 UTC 2024
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  5. A demo of the Spectral Biclustering algorithm —...

    This example demonstrates how to generate a checkerboard dataset and bicluster it using the SpectralBiclustering algorithm. The spectral biclustering algorithm is specifically designed to cluster d...
    scikit-learn.org/stable/auto_examples/bicluster/plot_spectral_biclustering.html
    Fri Nov 22 23:53:26 UTC 2024
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  6. SGD: Weighted samples — scikit-learn 1.5.2 docu...

    Plot decision function of a weighted dataset, where the size of points is proportional to its weight. Total running time of the script:(0 minutes 0.079 seconds) Launch binder Launch JupyterLite Dow...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_weighted_samples.html
    Fri Nov 22 23:53:27 UTC 2024
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  7. SVM Tie Breaking Example — scikit-learn 1.5.2 d...

    Tie breaking is costly if decision_function_shape='ovr', and therefore it is not enabled by default. This example illustrates the effect of the break_ties parameter for a multiclass classification ...
    scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html
    Fri Nov 22 23:53:26 UTC 2024
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  8. Sparse inverse covariance estimation — scikit-l...

    Using the GraphicalLasso estimator to learn a covariance and sparse precision from a small number of samples. To estimate a probabilistic model (e.g. a Gaussian model), estimating the precision mat...
    scikit-learn.org/stable/auto_examples/covariance/plot_sparse_cov.html
    Fri Nov 22 23:53:27 UTC 2024
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  9. Gaussian Process for Machine Learning — scikit-...

    Examples concerning the sklearn.gaussian_process module. Ability of Gaussian process regression (GPR) to estimate data noise-level Comparison of kernel ridge and Gaussian process regression Forecas...
    scikit-learn.org/stable/auto_examples/gaussian_process/index.html
    Fri Nov 22 23:53:26 UTC 2024
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  10. The Johnson-Lindenstrauss bound for embedding w...

    on the 20 newsgroups text document (TF-IDF word frequencies)...newsgroups dataset some 300 documents with 100k features in total...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_johnson_lindenstrauss_bound.html
    Fri Nov 22 23:53:26 UTC 2024
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